Work

Beyond optimality: Genetic Algorithms and Fuzzy Inference for Coil-Order allocation in the steel industry.

Year: 2025

Type: article

Abstract: The paper addresses the Coil-Order Allocation problem in steel industry via Genetic Algorithms through two approaches: a basic solution with a standard objective function and an advanced method incorporating a Fuzzy Inference System to mimic human decision-making. Both solutions were tested on real-world data from a tinplate production plant, achieving significant improvements in orders fulfillment and material utilization compared to manual allocation. The basic genetic approach outperforms the baseline in efficiency, while the fuzzy-genetic method demonstrate flexibility for complex, customizable optimization. The results show the potential of combining heuristic techniques and fuzzy logic to enhance industrial operations.

Source: IFAC-PapersOnLine

DOI: 10.1016/j.ifacol.2025.09.171

Authors: Marco Vannucci, Valentina Colla, Laura Laid, Erwin Sirovnik

Institutions: Scuola Superiore Sant'Anna, ThyssenKrupp (Germany)

Language: English

Topic: Scheduling and Optimization Algorithms

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

Funder: Research Fund for Coal and Steel